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dc.contributor.author
Echebest, Nélida Ester  
dc.contributor.author
Sanchez, María Daniela  
dc.contributor.author
Schuverdt, María Laura  
dc.date.available
2018-07-30T17:38:16Z  
dc.date.issued
2016-01  
dc.identifier.citation
Echebest, Nélida Ester; Sanchez, María Daniela; Schuverdt, María Laura; Convergence Results of an Augmented Lagrangian Method Using the Exponential Penalty Function; Springer/Plenum Publishers; Journal Of Optimization Theory And Applications; 168; 1; 1-2016; 92-108  
dc.identifier.issn
0022-3239  
dc.identifier.uri
http://hdl.handle.net/11336/53423  
dc.description.abstract
In the present research, an Augmented Lagrangian method with the use of the exponential penalty function for solving inequality constraints problems is considered. Global convergence is proved using the constant positive generator constraint qualification when the subproblem is solved in an approximate form. Since this constraint qualification was defined recently, the present convergence result is new for the Augmented Lagrangian method based on the exponential penalty function. Boundedness of the penalty parameters is proved considering classical conditions. Three illustrative examples are presented.  
dc.format
application/pdf  
dc.language.iso
eng  
dc.publisher
Springer/Plenum Publishers  
dc.rights
info:eu-repo/semantics/openAccess  
dc.rights.uri
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/  
dc.subject
Augmented Lagrangian Methods  
dc.subject
Constraint Qualifications  
dc.subject
Global Convergence  
dc.subject
Nonlinear Programming  
dc.subject
The Exponential Penalty Function  
dc.subject.classification
Matemática Pura  
dc.subject.classification
Matemáticas  
dc.subject.classification
CIENCIAS NATURALES Y EXACTAS  
dc.title
Convergence Results of an Augmented Lagrangian Method Using the Exponential Penalty Function  
dc.type
info:eu-repo/semantics/article  
dc.type
info:ar-repo/semantics/artículo  
dc.type
info:eu-repo/semantics/publishedVersion  
dc.date.updated
2018-07-30T13:37:23Z  
dc.journal.volume
168  
dc.journal.number
1  
dc.journal.pagination
92-108  
dc.journal.pais
Estados Unidos  
dc.journal.ciudad
Nueva York  
dc.description.fil
Fil: Echebest, Nélida Ester. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional de La Plata. Facultad de Ciencias Exactas. Departamento de Matemáticas; Argentina  
dc.description.fil
Fil: Sanchez, María Daniela. Universidad Nacional de La Plata. Facultad de Ciencias Exactas. Departamento de Matemáticas; Argentina  
dc.description.fil
Fil: Schuverdt, María Laura. Universidad Nacional de La Plata. Facultad de Ciencias Exactas. Departamento de Matemáticas; Argentina  
dc.journal.title
Journal Of Optimization Theory And Applications  
dc.relation.alternativeid
info:eu-repo/semantics/altIdentifier/doi/https://dx.doi.org/10.1007/s10957-015-0735-7  
dc.relation.alternativeid
info:eu-repo/semantics/altIdentifier/url/https://link.springer.com/article/10.1007%2Fs10957-015-0735-7